Data-Driven School Culture: Three Ways to Initiate Lasting Change

In one of our recent blogs, we talked about the role a visionary school leader can play when it comes to data-driven instruction—that of a data champion. Being a data champion means understanding how critical student performance data is in motivating teachers, informing instructional practices, and improving student learning.

Placing an importance on student data is just one aspect of a data champion’s role. A common challenge we see is when schools find themselves “data rich and information poor.”  They may have data, but they lack the processes and systems to collect, assess, analyze, and act on data in a meaningful way. 

A common challenge we see is when schools find themselves “data rich and information poor.” They may have data, but they lack the processes and systems to collect, assess, analyze, and act on data in a meaningful way. 

To truly drive school improvement, and ultimately, student achievement, school leaders need to create the conditions where a data-driven school culture can thrive. That means making it as easy and efficient as possible for your teachers and staff to use data to identify where students are struggling, examine the root cause of those challenges, and determine the best actions to keep students on track.

How do you make the shift from being an individual data champion to championing a school culture where data-driven decision making is at the forefront? It begins with the three actions we’ve outlined below:

Ensure your data-driven systems are in place

Think about the data collection and data analysis at your school as if you’re traveling to a destination with the help of your trusty GPS. Let’s say you accidentally miss your exit. What does your GPS do? It recalibrates. Armed with the new information of where you are currently, it quickly offers a revised route for you to take to get to the same destination. 

It's similar to how student performance data is used to inform instruction. At the beginning of the school year, you might pay attention to standards, learning goals, and summative tests to give you a starting point for your journey. Throughout the year, teachers need to be able to gauge student mastery to determine if students are indeed on track in meeting those learning goals, or if they’ll need to adjust course.

Just like taking a trip with your GPS, there needs to be a thoughtful, intentional approach to how you’ll get to your data destination—and this is where the data-driven instruction (DDI) cycle comes in.

Just like taking a trip with your GPS, there needs to be a thoughtful, intentional approach to how you’ll get to your data destination—and this is where the data-driven instruction (DDI) cycle comes in.

The DDI cycle is a continuous process of improved learning that builds over time. Typically, this process consists of four parts:

• Assessment: This is where educators gather information to assess student learning. There are many forms of assessment data, and schools work to collect the most timely and relevant data from multiple sources.
• Analysis: This is where you and your team can interpret the data you’ve collected, using a variety of tools, techniques, and collaborative conversations within PLCs or similar forums to identify patterns in the data—and then make informed decisions about what the data says about student performance and what will lead to better student outcomes. 
• Action: This is where you implement the targeted, strategic instructional changes you’ve discussed relative to the areas of need.
• Monitoring: This is where you and your team monitor and adjust to make sure students are progressing toward their learning goals. And, then repeat the cycle. 

The most important part of this cycle is that it happens continuously. Performing these four steps consistently—and getting into the groove of repeating it, over and over—is truly the foundation of the DDI cycle. And, also how continuous improvement becomes an integral part of your school culture. 

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Elevate your team’s data literacy

After you’ve done the work with your teachers and staff to set your school’s own standards for what the data-driven instructional cycle looks like, they’ll then need to know exactly what that means for them in their day-to-day instructional practice.

After you’ve done the work with your teachers and staff to set your school’s own standards for what the data-driven instructional cycle looks like, they’ll then need to know exactly what that means for them in their day-to-day classroom instruction.

This might also be the point where the data-driven instruction process becomes a little intimidating for some teachers. They may not feel 100 percent comfortable with reading and analyzing data—and that discomfort might lead to them feeling disengaged.

If you have teachers that fall into this category, consider how you might be able to increase their data literacy and their comfort level. Think about it through the lens of your own cycle of assessment, analysis, and action:

• First, assess your educators’ comfort with reading, writing, and communicating data. This might be rolled out through an anonymous survey, or simply asking them one-on-one in your next meeting. You might also observe individual teachers’ data literacy in team meetings to determine strengths and struggles in reviewing student data, finding meaning, and identifying next steps.
• Second, determine the type of professional development that’s needed to build data literacy. Here’s where it’s a good idea to identify the teachers and staff in your school that consider DDI to be a strength of theirs. 
• Then, engage in the PD through teacher-led professional learning. This type of learning can be administered through collaborative meetings, and it’s a win-win: not only are you able to give your teacher leaders ownership over their professional growth, but you’re creating professional learning that’s often more engaging than PD administered by a third-party. This adds to a strong data culture. 

No matter how you go about developing data literacy among your team, it’s important that everyone be talking about data in the same way. Establishing norms and a common language or terminology that teachers and staff can use when analyzing and discussing data will ensure that everyone’s starting at the same place. 

Start small to avoid overwhelm

Long-distance runners don’t typically train for a marathon by running 20 miles during their first training run. They build their mileage throughout their training schedule, starting with a baseline and increasing by a certain percentage as the weeks and months go by. Six months later, their last training run is almost the same amount as the 26.2 miles they’ll run during the actual race. 

Consider this metaphor as you’re working to develop your school’s data-driven culture. Inundating teachers with a myriad of numbers, charts, graphs, and qualitative data of student progress and growth will most likely overwhelm teachers, especially in the beginning of your DDI journey. 

If you’re new to data-driven instruction, the key is to start small. Have your teachers focus on one subject, or one of their classes, to begin their own DDI journey. Work on narrowing your focus and encourage your teams to think specifically about the key concepts or skills they want their students to master. Be sure to always prioritize the resulting changes that need to be made in instructional practices to achieve those learning outcomes. 

Be sure to always prioritize the resulting changes that need to be made in instructional practices to achieve those learning outcomes. 

Then, work outward to identify the data that needs to be collected, and how it will be organized. Ask your teachers: What formative assessments might they use to get the data they need? Can the data be gained in other ways, such as asking a series of simple questions at the end of a lesson—or the end of the school week? As the DDI cycle gets easier to manage, the adoption of more of these instructional cycles will come naturally. 

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Taking the time to build a data-driven foundation = lasting results

As school leaders, we can be quick to move to solutions. We’re eager to make changes, so we want to start moving as quickly as possible. However, we encourage you to take a bit of extra time to make sure you have these three actions firmly in place.

After all, you’re stacking the building blocks necessary to create lasting change at your school through data-driven instruction. That’s a huge undertaking, and one that requires a lot of thought around the systems you put in place. It means acting with consistency and intention.

To go fast, we often need to go slow—at least in the beginning. And it’s going slow that will pay dividends in helping students master what they need to learn.